Browse > Article

Analysis of Bloggers' Influence Style within Blog  

Tan, Luke Kien-Weng (Wee Kim Wee School of Communication & Information Nanyang Technological University)
Na, Jin-Cheon (Wee Kim Wee School of Communication & Information Nanyang Technological University)
Publication Information
Journal of Information Science Theory and Practice / v.1, no.2, 2013 , pp. 36-57 More about this Journal
Blogs are readily available sources of opinions and sentiments which allows bloggers to exert a certain level of influence over the blog readers. Previous studies had attempted to analyze blog features to detect influence within the blogosphere, but had not studied in details influence at the blogger-level. Other studies studied bloggers' personalities with regards to their propensity to blog, but did not relate the personalities of bloggers to influence. Bloggers may differ in their way or manner of exerting influence. For example, bloggers could be active participants or just passive shares, or whether they express ideas in a rational or subjective manner, or they are received positively or negatively by the readers. In this paper, we further analyze the engagement style (frequency, scope, originality, and consistency of the blog postings), persuasion style (appeals to reasons or emotions), and persona (degree of compliance) of individual bloggers. Methods used include similarity analysis to detect the sharing-creating aspect of engagement style, subjectivity analysis to measure persuasion style, and sentiment analysis to identify persona style. While previous studies analyzed influence at blog site level, our model is shown to provide a fine-grained influence analysis that could further differentiate the bloggers' influence style in a blog site.
Influence style; influence detection; blogger analysis;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Herring, S. C., Kouper, I., Paolillo, J. C., Scheidt, L. A., Tyworth, M., Welsch, P., Wright, E., & Yu, N. (2005). Conversations in the blogosphere: An analysis "from the bottom up." In Sprague, R. H. (Ed.), Proceedings of the Thirty-Eighth Hawaii International Conference on System Sciences, (pp. 107b). Los Alamitos: IEEE Press.
2 Hogg, M. A., & Vaughan, G. M. (2005). Social psychology. Harlow: Pearson/Prentice Hall.
3 Kelman, H. C. (1958). Compliance, identification, and internalization: Three processes of attitude change. Journal of Conflict Resolution, 2(1), 51-60.   DOI   ScienceOn
4 Krackhardt, D. (1992). The strength of strong ties: The importance of philos in organizations, 216-239. Boston, MA: Harvard Business School Press.
5 Leskovec, J., Huttenlocher, D., & Kleinberg, J. (2010). Predicting positive and negative links in online social networks. In M. Rappa, P. Jones, J. Freire, & S. Chakrabarti (Eds.), Proceedings of the 19th International Conference on World Wide Web (pp. 641-650). New York, NY: ACM Press.
6 Li, H., Bhowmick, S. S., & Sun, A. (2011). CASINO: Towards conformity-aware social influence analysis in online social networks. In B. Berendt, A. Vires, W. Fan, C. Macdonald, I. Ounis, I. Ruthven (Eds.), Proceedings of the 20th ACM International Conference on Information and Knowledge Management (pp. 1007-1012). New York, NY: ACM Press.
7 Mackie, D. M. (1987). Systematic and nonsystematic processing of majority and minority persuasive communications. Journal of Personality and Social Psychology, 53, 41-52.   DOI
8 Matsumura, N., Yamamoto, H. & Tomozawa, D. (2008). Finding influencers and consumer insights in the blogosphere. In E. Adar, M. Hurst, T. Finin, N. Glance, N. Nicolov, & B. Tseng (Eds.), Proceedings of International Conference on Weblogs and Social Media (pp. 76-83). California CA: AAAI Press.
9 Milgram, S. (1963). Behavioral study of obedience. Journal of Abnormal and Social Psychology, 67, 371-378.   DOI
10 Adar, E., & Adamic, L. A. (2005). Tracking information epidemics in blogspace. In A. Skowron, R. Agrawal, M. Luck, T. Yamaguchi, P. Morizet- Mahoudeaux, J. Liu, & N. Zhong (Eds.), Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (pp. 207-214). Washington, DC: IEEE Computer Society.
11 Agarwal, N., & Liu, H. (2008). Blogosphere: Research issues, tools, and applications, SIGKDD Explorations Newsletter, 10(1), 18-31.   DOI
12 Agarwal, N., Liu, H., Tang, L., & Yu, P.S. (2008). Identifying the influential bloggers in a community. In M. Najork, A. Broder, & S. Chakrabarti (Eds.), Proceedings of the International Conference on Web Search and Web Data Mining (pp. 207- 218). New York, NY: ACM Press.
13 Agarwal, N., & Liu, H. (2009). Modeling and Data Mining in Blogosphere. San Rafael, CA: Morgan & Claypool.
14 Brehm, J. W. (1966). A theory of psychological reactance. Academic Press.
15 Cai, K. K., Bao, S. H., Yang, Z., Tang, J., Ma, R., Zhang, L., & Su, Z. (2011). OOLAM: An Opinion Oriented Link Analysis Model for influence persona discovery. In I. King, W. Nejdl, & H. Li (Eds.), Proceedings of the 4th International Conference on Web Search and Data Mining, (pp. 645-654). New York, NY: ACM Press.
16 Cialdini, R. B. (2001). Influence: Science and practice (4th ed.). Boston: Allyn & Bacon.
17 Tan, L. K. W., Na, J.-C., Theng, Y.-L., & Chang, K. Y. (2012a). Phrase-level sentiment polarity classification using rule-based typed dependencies and additional complex phrases consideration. Journal of Computer Sciences and Technology, 27(3), 650- 666.   DOI
18 Somasundaran, S., & Wiebe, J. (2010), Recognizing stances in ideological on-line debates. In D. Inkpen, & C. Strapparava (Eds.), Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text (pp. 116-124). Stroudsburg, PA: ACL.
19 Song, X., Chi, Y., Hino, K., & Tseng, B. (2007), Identifying opinion leaders in the blogosphere. In A.H.F. Laender, A. O. Falcao, O. H.Olsen, M. J. Silva, R. Baeza-Yates, D. L. McGuiness, & B. Olstad (Eds.), Proceedings of the 16th ACM Conference on Information and Knowledge Management (pp. 971-974). New York, NY: ACM Press.
20 Tan, L. K. W., Na, J.-C., & Theng, Y.-L. (2011). Influence detection between blog posts through blog features, content analysis, and community identity, Online Information Review, 35(3), 425-442.   DOI   ScienceOn
21 Tan, L. K. W., Na, J.-C., Theng, Y.-L., & Chang, K. Y. (2012b). Profiling Blog Sites Through an Influence Style (INFUSE) Model (Manuscript submitted for publication).
22 Wiebe, J., Wilson, T., Bruce, R., Bell, M., & Martin, M. (2004). Learning subjective language. Computational Linguistics, 30, 277-308.   DOI   ScienceOn
23 Wilson, T., Wiebe J., & Hoffmann P. (2005). Recognizing contextual polarity in phrase-level sentiment analysis. In R.J. Mooney, C. Brew, L-F. Chien, K. Kirchhoff (Eds.), Proceedings of the Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (pp. 347-354). Stroudsburg, PA: ACL.
24 Costa, P. T., Jr., & McCrae, R. R. (1992). Normal personality assessment in clinical practice: The NEO personality inventory. Psychological Assessment, 4, 5-13.   DOI
25 Cialdini, R. B., & Goldstein, N. J. (2004). Social Influence: Compliance and conformity. Annual Review of Psychology, 55, 591-621.   DOI   ScienceOn
26 Cialdini, R. B., & Trost, M. R. (1998). Social influence: Social norms, conformity and compliance. In D.T. Gilbert, & S.T. Fiskel (Eds.). The handbook of social psychology (4th ed.), 2, 151-192. New York: McGraw- Hill.
27 Cohen, J. A. (1960). Coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20(1), 37-46.   DOI
28 Ghosh, R., & Lerman, K. (2008). Community detection using a measure of global influence. In L. Giles, J. Yen, H. Foley, M. Smith, & H. Zhang (Eds.), Proceedings of the 2nd SNA-KDD Workshop on Social Network Mining and Analysis (pp. 20-35). Berlin, Heidelberg: Springer-Verlag.
29 Granovetter, M. S. (1973). The strength of weak ties. The American Journal of Sociology, 78(6), 1360- 1380.   DOI   ScienceOn
30 Gruhl, D., Guha, R., Liben-Nowell, D., & Tomkins, A. (2004). Information diffusion through blogspace. In S. Feldman, M. Uretsky, M. Najork, & C. Wills (Eds.), Proceedings of the 13th International Conference on World Wide Web (pp. 491-501). New York, NY: ACM Press.
31 Guadagno, R. E., Okdie, B. M., & Eno, C. A. (2008). Who blogs? Personality predictors of blogging. Computers in Human Behavior, 24(5), 1993-2004.   DOI   ScienceOn
32 Herring, S. C., Scheidt, L. A., Bonus, S., & Wright, E. (2004). Bridging the gap: A genre analysis of weblogs. In Sprague, R.H. (Ed.), Proceedings of the 37th Hawaii International Conference on System Sciences. Los Alamitos: IEEE Computer Society Press.